Variable Pitch Camera for Autonomous Vehicle Detection
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Solution Overview
Problem
Conventional autonomous vehicles equipped with fixed-position cameras experience unreliable image reconstruction due to homogeneous texture backgrounds, leading to inaccurate lane detection and object recognition, which compromises road safety and maneuvering abilities.
Innovation Solution
The implementation of variable pitch cameras positioned at different locations and orientations on the autonomous vehicle, allowing dynamic adjustment of pitch angles based on distance, speed, and camera configurations to enhance image clarity and resolution for improved detection capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed-position cameras are used in autonomous vehicles, then device complexity is reduced, but image reconstruction accuracy deteriorates due to homogeneous texture backgrounds
Solution Approach 1:
The patent applies the dynamics principle by transitioning from fixed-position cameras to movable cameras that can dynamically adjust their positions and orientations. The camera system is mounted on movable platforms such as robotic arms or gimbals, enabling real-time repositioning to optimize image capture angles and avoid homogeneous texture backgrounds, thereby improving image reconstruction accuracy while maintaining manageable system complexity through automated control.
2Ease of operation
If fixed-position cameras are used, then ease of operation is improved, but lane detection accuracy deteriorates
Solution Approach 1:
The camera system dynamically adjusts its position and orientation to capture optimal views for lane detection. The movable platform allows the camera to pivot and reposition automatically based on detected scene characteristics, improving lane detection accuracy while the automated control system maintains ease of operation by eliminating manual adjustment requirements.
Solution Approach 2:
The system employs feedback mechanisms where image quality metrics and detection performance are continuously monitored. Based on this feedback, the camera automatically adjusts its position and orientation to optimize lane detection accuracy. The feedback loop ensures that the camera maintains optimal positioning without requiring manual intervention, balancing ease of operation with improved precision.
3Device complexity
If fixed-position cameras are used, then device complexity is reduced, but object detection reliability deteriorates in challenging environments
Solution Approach 1:
The movable camera system dynamically repositions itself to overcome challenging environmental conditions such as glare, shadows, or occlusions. By adjusting the camera's position and orientation in real-time, the system maintains reliable object detection across varying environments. The automated control ensures that the complexity increase is managed while achieving improved reliability.
Solution Approach 2:
The system changes key parameters including camera position, orientation, and potentially focal length to adapt to different environmental conditions. These parameter changes enable the camera to capture images with sufficient contrast and detail for reliable object detection, even in challenging lighting or weather conditions, while the automated system manages the complexity of these adjustments.
4Manufacturing precision
If fixed-position cameras are used, then manufacturing precision requirements are reduced, but trajectory control accuracy deteriorates
Solution Approach 1:
The movable camera system compensates for variations in manufacturing precision through dynamic repositioning. Instead of relying on perfectly precise fixed mounting, the system can adjust the camera's position and orientation during operation to achieve the required trajectory control accuracy. This reduces the stringency of manufacturing tolerances while maintaining high measurement precision through active adjustment.
Data Source
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AI summary
The invention provides an autonomous vehicle capable of driving independently through a path of intense traffic and transporting objects or people, even on rough surfaces, whilst ensuring safety of the vehicle and general road safety. The autonomous vehicle includes at least one variable pitch camera for producing images to be used for a computer vision to control the autonomous vehicle. The invention facilitates changing the pitch of the variable pitch camera to maximise camera image clarity and/or resolution as the autonomous vehicle moves. The images can be used for lane detection, pedestrian detection, three-dimensional (3D) reconstruction of an environment and/or pothole detection. With the invention, at least one image from the variable pitch camera is used in controlling the movement and/or the trajectory of the autonomous vehicle.